Hydrogel-based platforms for site-specific doxorubicin release in cancer therapy.

Hydrogels are promising candidates for the delivery of therapeutics in the treatment of human cancers. Regarding to the biocomaptiiblity, high drug and encapsulation efficacy and adjustable physico-chemical features, the hydrogels have been widely utilized for the delivery of chemotherapy drugs. Doxorubicin (DOX) is one of the most common chemotherapy drugs used in cancer therapy through impairing topoisomerase II function and increasing oxidative damage. However, the tumor cells have developed resistance into DOX-mediated cytotoxic impacts, requiring the delivery systems to increase internalization and anti-cancer activity of this drug. The hydrogels can deliver DOX in a sustained manner to maximize its anti-cancer activity, improving cancer elimination and reduction in side effects and drug resistance. The natural-based hydrogels such as chitosan, alginate and gelatin hydrogels have shown favourable biocompatibility and degradability in DOX delivery for tumor suppression. The hydrogels are able to co-deliver DOX with other drugs or genes to enhance drug sensitivity and mediate polychemotherapy, synergistically suppressing cancer progression. The incorporation of nanoparticles in the structure of hydrogels can improve the sustained release of DOX and enhancing intracellular internalization, accelerating DOX's cytotoxicity. Furthermore, the stimuli-responsive hydrogels including pH-, redox- and thermo-sensitive platforms are able to improve the specific release of DOX at the tumor site. The DOX-loaded hydrogels can be further employed in the clinic for the treatment of cancer patients and improving efficacy of chemotherapy.

NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to have high prognostic value in HCC, its application in clinical prognosis prediction requires specialized knowledge and complex calculations, which poses challenges for clinicians. It would be of interest to develop a model to help clinicians make full use of micronecrosis to assess patient survival. METHODS: To address these challenges, we propose a HCC prognosis prediction model that integrates pathological micronecrosis information through Graph Convolutional Neural Networks (GCN). This approach enables GCN to utilize micronecrosis, which has been shown to be highly correlated with prognosis, thereby significantly enhancing prognostic stratification quality. We developed our model using 3622 slides from 752 patients with primary HCC from the FAH-ZJUMS dataset and conducted internal and external validations on the FAH-ZJUMS and TCGA-LIHC datasets, respectively. RESULTS: Our method outperformed the baseline by 8.18% in internal validation and 9.02% in external validations. Overall, this paper presents a deep learning research paradigm that integrates HCC micronecrosis, enhancing both the accuracy and interpretability of prognostic predictions, with potential applicability to other pathological prognostic markers. CONCLUSIONS: This study proposes a composite GCN prognostic model that integrates information on HCC micronecrosis, collecting large dataset of HCC histopathological images. This approach could assist clinicians in analyzing HCC patient survival and precisely locating and visualizing necrotic tissues that affect prognosis. Following the research paradigm outlined in this paper, other prognostic biomarker integration models with GCN could be developed, significantly enhancing the predictive performance and interpretability of prognostic model.

Paeonol prevents sepsis-associated encephalopathy via regulating the HIF1A pathway in microglia.

Paeonol, a phenolic acid compound extracted from the Cortex Moutan, exhibits significant anti-inflammatory, antioxidant, and anti-apoptotic properties. This study aimed to investigate the effects of paeonol on neuroinflammation and depressive-like symptoms, and the underlying mechanisms in a mouse model of sepsis-associated encephalopathy (SAE) induced by lipopolysaccharide (LPS). To assess the therapeutic potential of paeonol in mice treated with LPS, behavioral assessments were conducted using the open-field test (OFT), tail suspension test (TST), and forced swimming test (FST), and quantitative PCR (qPCR), Western blot, and immunofluorescent staining were utilized to determine the expression levels of inflammatory molecules in the hippocampus in vivo and microglial cells in vitro. Our results revealed that paeonol significantly alleviated anxiety and depressive-like symptoms, as evidenced by improved activity in OFT, reduced immobility time in TST and FST, and decreased levels of inflammatory markers such as IL6, TNFα, and PFKFB3. Further in vitro experiments confirmed that paeonol downregulated the expression of pro-inflammatory molecules. A network pharmacology-based strategy combined with molecular docking and cellular thermal shift assay highlighted HIF1A as a potential target for paeonol. Similar anti-inflammatory effects of a HIF1A inhibitor were also observed in microglia treated with LPS. Furthermore, these effects were reversed by CoCl2, a HIF1A agonist, indicating the critical role of the HIF1A signaling pathway in mediating the therapeutic effects of paeonol. These findings highlight the potential of paeonol in modulating the HIF1A pathway, offering a promising therapeutic strategy for neuroinflammation in SAE.

Magnesium-promoted nickel-catalysed chlorination of aryl halides and triflates under mild conditions.

In this study, we present a ligand-free nickel(II)-catalyzed halogen exchange of aromatic halides with magnesium chloride. This method effectively facilitates the retro-Finkelstein reaction for a wide range of aryl bromides, iodides and triflates, demonstrating excellent functional group tolerance. Mechanistic studies reveal that magnesium plays a crucial role in the challenging reductive elimination from Ni(II) intermediates.

Adjustable Phase-Amplitude-Phase Acoustic Metasurface for the Implementation of Arbitrary Impedance Matrices.

Impedance metasurfaces enable accurate regulation of acoustic fields. However, they can hardly supply a flexible response as such perfect operation is accompanied by stringent requirements on the design of unit cells. Actually, an arbitrary lossless and passive target impedance matrix requires the tuning of 3 independent real parameters. The set composed of a reflection phase, a transmission amplitude, and a transmission phase, enables the representation of an arbitrary impedance matrix, possibly possessing singular elements. In this paper, a mechanism of phase-amplitude-phase modulation (PAP modulation) is developed for the generic design of the unit cells of acoustic impedance metasurfaces. Adjustable acoustic impedance metasurfaces are further available under this framework. An impedance unit with 3 mobile parts is designed based on this idea. The assembled metasurface can handle different incidences for acoustic field manipulation at a given frequency. Beam steering and beam splitting are considered as demonstration examples and are verified by numerical simulation and experiment. PAP modulation enriches the design of acoustic impedance metasurfaces and extends the range of application of impedance theory.

Cimifugin Alleviates Chronic Constriction Injury of the Sciatic Nerve by Suppressing Inflammatory Response and Schwann Cell Apoptosis.

Inflammation and Schwann cell apoptosis play critical roles in neuropathic pain after sciatic nerve injury. This study aimed to explore the function and mechanism of cimifugin in lipopolysaccharide (LPS)-stimulated rat Schwann cells and sciatic nerves of rats treated with chronic constriction injury (CCI). Thermal, mechanical and cold hyperalgesia of rats in response to cimifugin or mecobalamin (the positive drug control) treatment were evaluated through behavioral tests. H&E staining of sciatic nerves was performed for pathological observation. ELISA was conducted to assess concentrations of inflammatory cytokines in rat serum and sciatic nerves. The intensity of S100ß in sciatic nerves was determined using immunohistochemistry. Flow cytometry analysis was conducted for detection of Schwann cell apoptosis. RT-qPCR was performed to measure mRNA levels of inflammatory factors in Schwann cells. Immunofluorescence staining was performed to detect cellular p65/NF-κB activity. Western blotting was performed to quantify protein levels of apoptotic markers and factors associated with the NF-κB and MAPK pathways in rat nerves and Schwann cells. As shown by experimental data, cimifugin mitigated thermal, mechanical and cold hyperalgesia of CCI rats. Cimifugin repressed inflammatory cell infiltration, reduced proinflammatory cytokine levels while increasing anti-inflammatory factor (IL-10) level in serum or sciatic nerves of CCI rats. Cimifugin enhanced S100ß expression and downregulated apoptotic markers in vivo. The anti-inflammatory and anti-apoptotic properties of cimifugin were verified in the LPS-stimulated Schwann cells. Moreover, cimifugin suppressed nuclear translocation of p65 NF-κB in vitro and repressed the phosphorylation of IκB, p65 NF-κB, p38 MAPK, ERK1/2, as well as JNK in CCI rats. In conclusion, cimifugin alleviates neuropathic pain after sciatica by suppressing inflammatory response and Schwann cell apoptosis via inactivation of NF-κB and MAPK pathways.

The involvement of multiple ABC transporters in daunorubicin efflux in Streptomyces coeruleorubidus.

Streptomyces genus produces a large number of antibiotics, which are always synthesized by specific biosynthetic gene clusters (BGCs). To resist autotoxicity, transporters encoded by genes located within BGC occasionally pump antibiotic along with transporter encoded by gene located outside BGC. Daunorubicin is an anthracycline antibiotic biosynthesized by Streptomyces species, playing a crucial role in the treatment of leukaemia. In existing studies, only one two-component ATP-binding cassette (ABC) transporter, encoded by drrA1-drrB1 (abbreviated as drrAB1) and located within the daunorubicin BGC, has been proven to extrude daunorubicin. In this work, two other two-component ABC transporters, encoded by drrAB2 and drrAB3 and located outside the cluster, were found to play the complementary role in daunorubicin efflux in S. coeruleorubidus. Disruption of three drrABs resulted in a 94% decrease in daunorubicin production. Furthermore, drrAB2 is regulated by the TetR family regulator DrrR1, responding to the intracellular accumulation of daunorubicin and suggesting its role in stress response and self-resistance. Although the homologues of DrrAB1 are only found in three anthracycline BGCs, the homologues of DrrAB2 and DrrAB3 are spread in many Streptomyces strains which do not contain any known anthracycline BGC. This indicates that DrrAB2 and DrrAB3 may recognize and extrude a broader range of substrates besides daunorubicin, thus playing a more extensive role in cellular detoxification.

One-Step Construction of Hierarchical Porous and Defect-Rich Zn2+-Doped NH2-MIL-125(Ti) to Enhance Photocatalytic Degradation of Tetracycline Hydrochloride.

The development of efficient metal-organic framework (MOF) photocatalysts for the degradation of tetracycline hydrochloride (TC) is crucial for environmental and public health. Herein, NH2-MIL-125(Ti) flakes (namely, ZnxTi1-x-NML), featuring defect-rich and Zn2+-doping, were synthesized using a one-step solvothermal method. For the first time, the crystal structure of Zn-doped NML was determined by combining extended X-ray absorption with fine structure spectroscopy. The formation mechanisms of the flake morphology with hierarchical porous structures were thoroughly investigated. Compared to NH2-MIL-125(Ti), Zn0.15Ti0.85-NML achieved a 3.4-fold increase in removal of TC under simulated sunlight. The adjusted electronic structure enhances superoxide radical production, coupled with a flake-like and porous architecture that promotes reaction sites, improved mass transfer, and reduced charge distances. Combined with theoretical calculations of the density of states and electrostatic potential, the ligand-metal-metal charge transfer process was elucidated. The possible pathway for the photocatalytic degradation of TC by Zn0.15Ti0.85-NML was further speculated. Moreover, the safety of the photocatalytic pathway was assessed by predicting the toxicity of the degradation intermediates. Our findings link the structure of MOFs to their catalytic efficiency, guiding the creation of sustainable photocatalysts.

Stabilization of RRBP1 mRNA via an m6A-dependent manner in prostate cancer constitutes a therapeutic vulnerability amenable to small-peptide inhibition of METTL3.

Mounting evidence has implicated the RNA m6A methylation catalyzed by METTL3 in a wide range of physiological and pathological processes, including tumorigenesis. The detailed m6A landscape and molecular mechanism of METTL3 in prostate cancer (PCa) remains ill-defined. We find that METTL3 is overexpressed in PCa and correlates with worse patient survival. Functional studies establish METTL3 as an oncoprotein dependent on its m6A enzymatic activity in both AR+ and AR- PCa cells. To dissect the regulatory network of m6A pathway in PCa, we map the m6A landscape in clinical tumor samples using m6A-seq and identify genome-wide METTL3-binding transcripts via RIP-seq. Mechanistically, we discover RRBP1 as a direct METTL3 target in which METTL3 stabilizes RRBP1 mRNA in an m6A-dependent manner. RRBP1 positively correlates with METTL3 expression in PCa cohorts and exerts an oncogenic role in aggressive PCa cells. Leveraging the 3D structural protein-protein interaction between METTL3 and METTL14, we successfully develop two potential METTL3 peptide inhibitors (RM3 and RSM3) that effectively suppress cancer cell proliferation in vitro and tumor growth in vivo. Collectively, our study reveals a novel METTL3/m6A/RRBP1 axis in enhancing aggressive traits of PCa, which can be therapeutically targeted by small-peptide METTL3 antagonists.

Role of TREM2 in immune and neurological diseases: Structure, function, and implications.

Triggering Receptor Expressed on Myeloid Cells 2 (TREM2), a transmembrane receptor initially linked to neurodegenerative diseases, has recently emerged as a key player in conditions such as obesity and cancer. This review explores the structure, function, and mechanisms of TREM2 across these diverse pathological contexts, with a particular focus on its critical roles in immune regulation and neuroprotection. TREM2 primarily modulates cellular activity by binding extracellular ligands, thereby activating downstream signaling pathways and exerting immunomodulatory effects. Additionally, the therapeutic potential of targeting TREM2 is discussed, emphasizing its promise as a future treatment strategy for various diseases.

Dietary inflammatory index and all-cause mortality in adults with COPD: a prospective cohort study from the NHANES 1999-2018.

Background: Chronic inflammation is closely linked to Chronic Obstructive Pulmonary Disease (COPD); however, the impact of the Dietaryq Inflammatory Index (DII) on mortality among COPD patients remains uncertain. Objective: To assess the correlation between the DII and all-cause mortality in COPD patients using data from the National Health and Nutrition Examination Survey (NHANES). Methods: We conducted a retrospective cohort study on 1,820 COPD patients from the NHANES dataset (1999-2018). The influence of DII on mortality was evaluated using multivariate Cox regression, smoothing spline fitting, and threshold effect analysis. Additionally, Kaplan-Meier survival analysis was performed to compare survival curves among different DII groups. Subgroup analyses and E-values identified sensitive cohorts and assessed unmeasured confounding. Results: Over an average follow-up of 91 months, multivariate Cox regression models revealed a significant positive correlation between DII scores and mortality risk, with each unit increase in DII associated with a 10% higher risk of death (HR: 1.10, 95% CI: 1.03-1.16; P = 0.002). Among the DII tertiles, individuals in the second tertile (T2: 1.23-2.94) experienced a 67% increase in mortality risk compared to those in the lowest tertile (T1: -5.28-1.23) (HR: 1.67, 95% CI: 1.26-2.21; p < 0.001). The third tertile (T3) did not show a statistically significant increase in mortality risk (HR: 1.30, 95% CI: 0.98-1.72; p=0.074). A restricted cubic spline analysis indicated a significant nonlinear association between DII and all-cause mortality (p = 0.021). Threshold effect analysis further revealed that below a DII of 2.19, there was a significant increase in all-cause mortality risk (HR = 1.19, 95% CI: 1.07-1.33; p = 0.002), while at or above this threshold, the risk increase was not statistically significant (HR=0.89, 95% CI: 0.68-1.15; p = 0.380). Kaplan-Meier analysis revealed significant differences in survival curves among DII tertiles (p < 0.001), with the lowest DII tertile showing the highest survival probability. Both subgroup and sensitivity analyses confirmed the robustness of these findings. Conclusion: DII is positively correlated with mortality risk in COPD patients, showing nonlinear characteristics and threshold effects, underscoring its prognostic value.

Translation Consistent Semi-supervised Segmentation for 3D Medical Images.

3D medical image segmentation methods have been successful, but their dependence on large amounts of voxel-level annotated data is a disadvantage that needs to be addressed given the high cost to obtain such annotation. Semi-supervised learning (SSL) solves this issue by training models with a large unlabelled and a small labelled dataset. The most successful SSL approaches are based on consistency learning that minimises the distance between model responses obtained from perturbed views of the unlabelled data. These perturbations usually keep the spatial input context between views fairly consistent, which may cause the model to learn segmentation patterns from the spatial input contexts instead of the foreground objects. In this paper, we introduce the Translation Consistent Co-training (TraCoCo) which is a consistency learning SSL method that perturbs the input data views by varying their spatial input context, allowing the model to learn segmentation patterns from foreground objects. Furthermore, we propose a new Confident Regional Cross entropy (CRC) loss, which improves training convergence and keeps the robustness to co-training pseudo-labelling mistakes. Our method yields state-of-the-art (SOTA) results for several 3D data benchmarks, such as the Left Atrium (LA), Pancreas-CT (Pancreas), and Brain Tumor Segmentation (BraTS19). Our method also attains best results on a 2D-slice benchmark, namely the Automated Cardiac Diagnosis Challenge (ACDC), further demonstrating its effectiveness. Our code, training logs and checkpoints are available at https://github.com/yyliu01/ TraCoCo.

Identification of potent biparatopic antibodies targeting FGFR2 fusion driven cholangiocarcinoma.

Translocations involving FGFR2 gene fusions are common in cholangiocarcinoma and predict response to FGFR kinase inhibitors. However, the rate and durability of response are limited due to the emergence of resistance, typically involving acquired FGFR2 kinase domain mutations, and to sub-optimal dosing, relating to drug adverse effects. Here, we report the development of biparatopic antibodies targeting the FGFR2 extracellular domain (ECD), as candidate therapeutics. Biparatopic antibodies can overcome drawbacks of standard bivalent monoparatopic antibodies, which often show poor inhibitory or even agonist activity against oncogenic receptors. We show that oncogenic transformation by FGFR2 fusions requires an intact ECD. Moreover, by systematically generating biparatopic antibodies that target distinct epitope pairs along the FGFR2 ECD, we identified antibodies that effectively block signaling and malignant growth driven by FGFR2-fusions. Importantly, these antibodies demonstrate efficacy in vivo, synergy with FGFR inhibitors, and activity against FGFR2 fusions harboring kinase domain mutations. Thus, biparatopic antibodies may serve as new treatment options for patients with FGFR2-altered cholangiocarcinoma. Summary: We identify biparatopic FGFR2 antibodies that are effective against FGFR2 fusion driven cholangiocarcinoma.

Research on marine flexible biological target detection based on improved YOLOv8 algorithm.

To address the challenge of suboptimal object detection outcomes stemming from the deformability of marine flexible biological entities, this study introduces an algorithm tailored for detecting marine flexible biological targets. Initially, we compiled a dataset comprising marine flexible biological subjects and developed a Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm, supplemented with a boundary detection enhancement module, to refine underwater image quality and accentuate the distinction between the images' foregrounds and backgrounds. This enhancement mitigates the issue of foreground-background similarity encountered in detecting marine flexible biological entities. Moreover, the proposed adaptation incorporates a Deformable Convolutional Network (DCN) network module in lieu of the C2f module within the YOLOv8n algorithm framework, thereby augmenting the model's proficiency in capturing geometric transformations and concentrating on pivotal areas. The Neck network module is enhanced with the RepBi-PAN architecture, bolstering its capability to amalgamate and emphasize essential characteristics of flexible biological targets. To advance the model's feature information processing efficiency, we integrated the SimAM attention mechanism. Finally, to diminish the adverse effects of inferior-quality labels within the dataset, we advocate the use of WIoU (Wise-IoU) as a bounding box loss function, which serves to refine the anchor boxes' quality assessment. Simulation experiments show that, in comparison to the conventional YOLOv8n algorithm, our method markedly elevates the precision of marine flexible biological target detection.

Identification, isoform classification, ligand binding, and database construction of the protein-tyrosine sulfotransferase family in metazoans.

Protein tyrosine sulfonation (PTS) influences various crucial physiological and pathological processes in animals. Protein-tyrosine sulfotransferase (TPST) serves as a pivotal enzyme in this process. Research on TPST is still in its early stages, and current identification methods have not yet effectively differentiated TPST from other type II sulfotransferases. Furthermore, this study has revealed that TPST in animals is highly conserved and exhibits significant differences when compared to other sulfotransferases and TPSTs in non-animal species. However, precise and efficient methods for identifying TPST, conducting subfamily classification, performing functional and sequence analyses, and accessing corresponding databases and analytical platforms for the entire TPST family of metazoan species are lacking. These findings provide a foundation for more in-depth research on TPST in animals and are crucial for advancing the understanding of PTS and its broader impacts. In this study, a Hidden Markov Model (TPST-HMM) was formulated based on the conserved motifs binding to the substrate PAPS and the ligand tyrosine in metazoan TPSTs. TPST-HMM successfully identified more than 91.8 % of metazoan TPSTs in UniProt (e-value < 1e-5). When the threshold was adjusted to 1e-20, the identification rate of TPST was 83.9 % in metazoans and approximately 0 % in other species (fungi, bacteria, etc.). Subsequently, 5638 TPSTs were identified from 1311 metazoan genomes, and these TPSTs were classified into three subfamilies. The classification of the TPST1 and TPST2 subtypes, which were initially annotated in mammals, was extended across vertebrates. Additionally, a novel subtype, TPST3, belonging to a distinct subfamily, was discovered in invertebrates. We proposed a molecular docking prediction method for TPST and tyrosine ligands based on the observation that TPST-tyrosine binding recognition and binding in metazoans were primarily driven by electrostatic interactions. Finally, a database website for animal TPST sequences was established (http://sz.bjfskj.com/). The website included an online tool for identifying TPST protein sequences, enabling annotation and visualization of functional motifs and active amino acids. Its design aimed to assist users in studying TPST in animals.

Self-Microemulsifying Drug Delivery System to Enhance Oral Bioavailability of Berberine Hydrochloride in Rats.

Berberine hydrochloride (BH) is a versatile bioactive compound derived from the plants of the Berberis genus, known for its various pharmacological effects. However, its oral bioavailability is low due to its high hydrophilicity and limited permeability. To enhance its clinical efficacy and oral bioavailability, this study designed and prepared a BH-loaded self-microemulsifying drug delivery system (BH-SMEDDS), and characterized its in vitro and in vivo properties. Firstly, the optimal formulation of BH-SMEDDS was selected using solubility evaluations, pseudo-ternary phase diagrams, and particle size analysis. The formulation containing 55% Capmul MCM, 22.5% Kolliphor RH 40, and 22.5% 1,2-propanediol was developed. BH-SMEDDS exhibited stable physicochemical properties, with an average particle size of 47.2 ± 0.10 nm and a self-emulsification time of 26.02 ± 0.24 s. Moreover, in vitro dissolution studies showed significant improvements in BH release in simulated intestinal fluid, achieving 93.1 ± 2.3% release within 300 min. Meanwhile, BH-SMEDDS did not exhibit cytotoxic effects on the Caco-2 cells. Additionally, BH-SMEDDS achieved a 1.63-fold increase in oral bioavailability compared to commercial BH tablets. Therefore, SMEDDS presents a promising strategy for delivering BH with enhanced oral bioavailability, demonstrating significant potential for clinical application.

Development of chemiluminescent systems and devices for analytical applications.

Chemiluminescence (CL) refers to the light-emitting phenomenon resulting from chemical reactions. Due to its simplicity in terms of instrumentation and high sensitivity, CL plays a critical role in analytical chemistry and has developed rapidly in recent years. In this review, we discuss the efforts made by our group in the field of CL. This includes exploring new luminophores that function under neutral pH conditions, developing oxidant- and reactive oxygen species-based coreactants (e.g. artemisinin and thiourea dioxide) for luminol and lucigenin CL, utilizing nanomaterial-based CL signal amplification and employing innovative ultrasound devices for CL and their analytical applications. We discussed the CL amplification mechanisms of these systems in detail. Finally, we summarize the challenges and prospects for the future development of CL.

Lateral/caudal ganglionic eminence makes limited contribution to cortical oligodendrocytes.

The emergence of myelinating oligodendrocytes represents a pivotal developmental milestone in vertebrates, given their capacity to ensheath axons and facilitate the swift conduction of action potentials. It is widely accepted that cortical oligodendrocyte progenitor cells (OPCs) arise from medial ganglionic eminence (MGE), lateral/caudal ganglionic eminence (LGE/CGE), and cortical radial glial cells (RGCs). Here, we used two different fate mapping strategies to challenge the established notion that the LGE generates cortical OPCs. Furthermore, we used a Cre/loxP-dependent exclusion strategy to reveal that the LGE/CGE does not give rise to cortical OPCs. Additionally, we showed that specifically eliminating MGE-derived OPCs leads to a significant reduction of cortical OPCs. Together, our findings indicate that the LGE does not generate cortical OPCs, contrary to previous beliefs. These findings provide a new view of the developmental origins of cortical OPCs and a valuable foundation for future research on both normal development and oligodendrocyte-related disease.